DocumentCode :
474539
Title :
Efficient Monte Carlo based incremental statistical timing analysis
Author :
Veetil, Vineeth ; Sylvester, Dennis ; Blaauw, David
Author_Institution :
EECS Dept., Univ. of Michigan, Ann Arbor, MI
fYear :
2008
fDate :
8-13 June 2008
Firstpage :
676
Lastpage :
681
Abstract :
Modeling and accuracy difficulties exist with traditional SSTA analysis and optimization methods. In this paper we describe methods to improve the efficiency of Monte Carlo-based statistical static timing analysis. We propose a Stratification + Hybrid Quasi Monte Carlo (SH- QMC) approach to reduce the number of samples required for Monte Carlo based SSTA. Our simulations on benchmark circuits up to 90 K gates show that the proposed method requires 23.8X fewer samples on average to achieve comparable accuracy in timing estimation as a random sampling approach. Results on benchmark circuits also show that when SH-QMC is performed with multiple parallel threads on a quad core processor, the approach is faster than traditional SSTA with comparable accuracy. SH-QMC scales better than traditional SSTA with circuit size. We also propose an incremental approach to recompute a percentile delay metric after ECO. The results show that on average only 1.4% and 0.7% of original samples need to be evaluated for exact recomputation of the 95 percentile and 99 percentile delays, after sample size reduction using SH-QMC.
Keywords :
CMOS integrated circuits; Monte Carlo methods; benchmark testing; integrated circuit modelling; statistical analysis; technology CAD (electronics); Monte Carlo simulations; benchmark circuits; computer-aided design tools; incremental statistical timing analysis; multiple parallel threads; nanometer-scale CMOS; percentile delay metric; variance reduction; Analysis of variance; Circuits; Delay estimation; Design automation; Monte Carlo methods; Optimization methods; Runtime; Sampling methods; Timing; Yield estimation; Monte Carlo; Statistical timing; Variance reduction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Design Automation Conference, 2008. DAC 2008. 45th ACM/IEEE
Conference_Location :
Anaheim, CA
ISSN :
0738-100X
Print_ISBN :
978-1-60558-115-6
Type :
conf
Filename :
4555905
Link To Document :
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